Triple
T13203750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sailortown area |
E314304
|
entity |
| Predicate | hasSocialCharacter |
P11720
|
FINISHED |
| Object | working-class roots |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: working-class roots | Statement: [Sailortown area, hasSocialCharacter, working-class roots]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSocialCharacter Context triple: [Sailortown area, hasSocialCharacter, working-class roots]
-
A.
hasSocialDimension
Indicates that the relationship, attribute, or phenomenon involves social aspects, interactions, or implications among individuals or groups.
-
B.
hasSocialIdentity
chosen
Indicates that an entity possesses or is associated with a particular social identity, such as a role, group membership, or socially recognized status.
-
C.
hasSocialService
Indicates that an entity provides, offers, or is associated with a social service to another entity or community.
-
D.
hasSocialEngagement
Indicates that an entity participates in or maintains some form of social interaction, activity, or relationship with others.
-
E.
sharesCharacterWith
Indicates that two entities have at least one character (such as a letter, symbol, or glyph) in common.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c9961a48190a1157df47f59b7af |
completed | April 10, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69d98bc938f081909f123bdf1263ff7f |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:17 p.m.